Spatial distribution characteristics and prediction of fluorine concentration in groundwater based on driving factors analysis

Groundwater suitability assessment for irrigation and drinking purposes by integrating spatial analysis, machine learning, water quality index, and health risk model

An in-depth understanding of nitrate-contaminated surface water and groundwater quality and associated risks is important for groundwater management. Hydrochemical characteristics and driving forces of groundwater quality and non-carcinogenic risks of nitrate were revealed by the integrated approaches of self-organizing map analysis, spatial visualization by geography information system, entropy and irrigation water quality indices, and human health risk model. Groundwater samples were categorized into two clusters by SOM analysis. Cluster I including three samples were Ca-SO4 type and cluster II of remaining 136 samples were Ca-HCO3 type. Hydrochemical compositions of two cluster samples were dominated by water-rock interaction: (1) calcite and gypsum dissolution for cluster I samples and (2) calcite dissolution, silicate weathering, and positive cation exchange for cluster II samples. Nitrate contamination occurred in both cluster I and II samples, primarily induced by agricultural nitrogen fertilizer. The EWQI results showed that 90.97% in total groundwater samples were suitable for drinking purpose, while the IWQI results demonstrated that 65.03% in total groundwater samples were appropriate for irrigation purpose. The HHR model and Monte Carlo simulation indicated that the non-carcinogenic nitrated risk was highest in children. Exposure frequency was the most sensitive factor (86.33% in total) influencing the total non-carcinogenic risk, indicated by sensitivity analysis. Compared with the two clusters of groundwater, surface water has a shorter circulation cycle and lower ion concentrations resulting in better water quality. This study can provide scientific basis for groundwater quality evaluation in other parts of the world.

Prediction of sulfate concentrations in groundwater in areas with complex hydrogeological conditions based on machine learning

The persistent and increasing levels of sulfate due to a variety of human activities over the last decades present a widely concerning environmental issue. Understanding the controlling factors of groundwater sulfate and predicting sulfate concentration is critical for governments or managers to provide information on groundwater protection. In this study, the integration of self-organizing map (SOM) approach and machine learning (ML) modeling offers the potential to determine the factors and predict sulfate concentrations in the Huaibei Plain, where groundwater is enriched with sulfate and the areas have complex hydrogeological conditions. The SOM calculation was used to illustrate groundwater hydrochemistry and analyze the correlations among the hydrochemical parameters. Three ML algorithms including random forest (RF), support vector machine (SVM), and back propagation neural network (BPNN) were adopted to predict sulfate levels in groundwater by using 501 groundwater samples and 8 predictor variables. The prediction performance was evaluated through statistical metrics (R2, MSE and MAE). Mine drainage mainly facilitated increase in groundwater SO42- while gypsum dissolution and pyrite oxidation were found another two potential sources. The major water chemistry type was Ca-HCO3. The dominant cation was Na+ while the dominant anion was HCO3-. There was an intuitive correlation between groundwater sulfate and total dissolved solids (TDS), Cl-, and Na+. By using input variables identified by the SOM method, the evaluation results of ML algorithms showed that the R2, MSE and MAE of RF, SVM, BPNN were 0.43-0.70, 0.16-0.49 and 0.25-0.44. Overall, BPNN showed the best prediction performance and had higher R2 values and lower error indices. TDS and Na+ had a high contribution to the prediction accuracy. These findings are crucial for developing groundwater protection and remediation policies, enabling more sustainable management.

Analysis of the distribution across media, migration, and related driving factors of fluoride in cold and arid lakes during the freezing period

Fluoride pollution in water has become a global challenge. This challenge especially affects China as a country experiencing serious fluoride pollution. While the have been past studies on the spatial distribution of fluoride, there has been less attention on different forms of fluoride. This study collected 176 samples (60, 40, and 76 ice, water, and sediment samples, respectively) from Lake Ulansuhai during the freezing period. The occurrence and spatial distribution characteristics of fluoride in lake ice-water-sediment were explored using Kriging interpolation, Piper three-line diagram, and Gibbs diagram analysis methods. The migration and transformation of fluoride during the freezing period were revealed and the factors influencing fluoride concentration in the water body were discussed considering the hydrochemical characteristics of lake surface water. The results showed that the average fluoride concentrations in the upper ice, middle ice and lower ice were 0.18, 0.09, and 0.12 mg/L, respectively, decreasing from north to south in the lake. The average concentrations of fluoride in surface water and bottom water were 0.63 and 0.83 mg/L, respectively. The concentrations of fluoride in ice and water were within the World Health Organisation drinking water threshold of 1.50 mg/L and the Class III Chinese surface water standard (GB3838-2002). The average sediment total fluorine was 1344.38 ± 200 mg/kg, significantly exceeding the global average (321 mg/kg) and decreasing with depth. The contents of water soluble, exchangeable, Fe/Mn bound, organic bound, and residual fluorides were 40.22-47.18, 13.24-43.23, 49.52-160.48, and 71.59-173.03 mg/kg, respectively. There was a significant positive correlation between fluoride concentration in ice and that in water. The change in fluoride concentration in water was mainly due to specific climatic and geographical conditions, pH, hydrochemical characteristics and ice sealing. This study is of great significance for the management of high-fluorine lakes in arid and semi-arid areas.

A new insight into fluoride induces cardiotoxicity in chickens: Involving the regulation of PERK/IRE1/ATF6 pathway and heat shock proteins

Fluorosis poses a significant threat to human and animal health and is an urgent public safety concern in various countries. Subchronic exposure to fluoride has the potential to result in pathological damage to the heart, but its potential mechanism requires further investigation. This study investigated the effects of long-term exposure to sodium fluoride (0, 500, 1000, and 2000 mg/kg) on the hearts of chickens were investigated. The results showed that an elevated exposure dose of sodium fluoride led to congested cardiac tissue and disrupted myofiber organisation. Sodium fluoride exposure activated the ERS pathways of PERK, IRE1, and ATF6, increasing HSP60 and HSP70 and decreasing HSP90. The NF-κB pathway and the activation of TNF-α and iNOS elicited an inflammatory response. BAX, cytc, and cleaved-caspase3 were increased, triggering apoptosis and leading to cardiac injury. The abnormal expression of HSP90 and HSP70 affected the stability and function of RIPK1, RIPK3, and MLKL, which are crucial necroptosis markers. HSPs inhibited TNF-α-mediated necroptosis and apoptosis of the death receptor pathway. Sodium fluoride resulted in heart injury in chickens because of the ERS and variations in HSPs, inducing inflammation and apoptosis. Cardiac-adapted HSPs impeded the activation of necroptosis. This paper may provide a reference for examining the potential cardiotoxic effects of sodium fluoride.

Hydrochemistry, quality, and integrated health risk assessments of groundwater in the Huaibei Plain, China

Groundwater is an essential freshwater resource utilized in industry, agriculture, and daily life. In the Huaibei Plain (HBP), where groundwater significantly influences socio-economic development, information about its quality, hydrochemistry, and related health risks remains limited. We conducted a comprehensive groundwater sampling in the HBP and examined its rock characteristics, water quality index (WQI), and potential health risks. The results revealed that the primary factors shaping groundwater hydrochemistry were rock dissolution and weathering, cation exchange, and anthropogenic activities. WQI assessment indicated that only 73% of the groundwaters is potable, as Fe2+, Mn2+, NO3-, and F- contents in the water could pose non-carcinogenic hazards to humans. Children were more susceptible to these health risks through oral ingestion than adults. Uncertainty analysis indicated that the probabilities of non-carcinogenic risk were approximately 57% and 31% for children and adults, respectively. Sensitivity analysis further identified fluoride as the primary factor influencing non-carcinogenic risks, indicating that reducing fluoride contamination should be prioritized in future groundwater management in the HBP.